ambient and cognitive networks youn-hee han [email protected] korea university of technology and...
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Ambient and Cognitive Networks
Youn-Hee [email protected]
Korea University of Technology and EducationInternet Computing Laboratory
http://icl.kut.ac.kr
2008 KREONET Workshop
EU’s FP6 (6th Framework Program) 유럽연합의 6 차 연구개발 프로그램 (2002~2006) Goal & Vision
유럽단일연구공간 (ERA: European Research Area) 의 실현 유럽의 과학기술 지형과 역량을 단일한 연구 공간 및 역량으로 통합 유럽을 21 세기 최고의 지식사회로 구축하고자 함 실질적인 유럽통합을 실현할 정책적 툴로 활용
주요 내용 및 예산
EU’s FP6
3/30
구분 내용 예산 (Euro)
연구 활동의 집중과 통합 사업
7 개 중점 연구 분야 핵심 연구 사업
132.85 억( 전체 예산의 3/4)
합동연구센터 사업7 개 중점 연구 분야에서 이루어지는 연구 개발 활동을 보완
2.9 억
ERA 구조화 인적자원 및 교류 , 연구인프라 26.55 억
ERA 기반강화 연구사업 조정 , 정책 개발 3.3 억
원자력 에너지 핵융합 , 방사성 폐기물 9.4 억
계 (2002 ~ 2006) 175 억 Euro (EU 전체 예산의 4%)
2008 KREONET Workshop
7 개 중점 연구 분야와 IST, WWI, Ambient Networks 의 관계
EU’s FP6 & Ambient and Cognitive Networks
4/30
연구 분야 예산 (Euro)
1. 생명과학 , 게노믹스 , 생명공학 22 억
2. 정보사회기술(Information Society Technologies, IST)
36 억
3. 나노기술 및 나노과학 , 새로운 생산공정 및 디바이스 13 억
4. 항공우주 10.75 억
5. 식품의 질 및 안전성 6.85 억
6. 지속가능한 발전 , 전지구적 변화 및 생태계 21.2 억
7. 지식기반사회에서의 시민과 통치 2.25 억
기타 13.2 억
계 132.85 억
…
WWI (Wireless World Initiative, 2004~)
yyyXXX
[IST 내의 통합 관리 프로젝트 ]
Ambient Network
Cognitive Network
2008 KREONET Workshop
Ambient Networks (AN) The name of a project within EU’s FP6 A software-driven dynamic network integration solution
Design Paradigm of AN To support network composition, mobility, multiple radio
interfaces, context awareness To offer common control functions to a wide range of
different applications and air interface technologies
Overview of Ambient Networks
5/30
[Ambient]: existing or present on all sides: of the surrounding area or environment
2008 KREONET Workshop
Four innovations of AN
Overview of Ambient Networks
6/30
Network Composition
Enhanced Mobility
Network Heterogeneity Support
Context Awareness
+
2008 KREONET Workshop
Ambient Control Space & Network Composition
Technology of Ambient Networks
8/30
Ambient Network Interface (ANI): Standardized single interface to connect the network instead of just connection of nodes: Offer a simple plug & play connection
Ambient Service Interfaces (ASI): Even in a composed Ambient Network, only a single homogeneous control space is visible to external entities : An application or service will always find the same environment
2008 KREONET Workshop
Ambient Control Space & Network Composition
Technology of Ambient Networks
9/30
GANS: Generic Ambient Networks Signalling Overlay Control Space
2008 KREONET Workshop
Generic Link layer (GLL) for a Multi-Radio Access
Technology of Ambient Networks
10/30
Generic Link Interface (GLI): It provides compatible radio link layers for different radio access technologies: A reconfiguration of the GLL (generic link layer) due to a change of radio access technology will be seamless
2008 KREONET Workshop
Scenario 1
Scenario 2
Scenarios of Ambient Networks
11/30
3G Base Station
Sensor NodeSink Node
WiMax/WiBro RAS (Base Station)
2008 KREONET Workshop
Active Research and Much Results
Instant Media Services for Users on the Move
Research Results of Ambient Networks
13/30
M. Vorwerk, S. Schuetz, R. Aguero, J. Choque, S. Schmid, M. Kleis, M. Kampmann, M. Erkoc, “Ambient networks in practice - instant media services for users on the move,” 2nd International Conference on TRIDENTCOM, 2006.
2008 KREONET Workshop
Active Research and Much Results New Handover Strategy & Business Map
Research Results of Ambient Networks
14/30
P. Poyhonen, J. Tuononen, T. Haitao, O. Strandberg, “Study of Handover Strategies for Multi-Service and Multi-Operator Ambient Networks,” 2nd International Conference on CHINACOM, 2007.
DS: Discovered Sets (of Access Networks)CST: Candidate Sets based on Terminal’s policy CSN: Candidate Sets based on Network’s policy AS: Finally selected Active Sets
Business Map
2008 KREONET Workshop
Active Research and Much Results Ambient Network Advertising Broker
Research Results of Ambient Networks
15/30
L. Ho, J. Markendahl, M. Berg, “Business Aspects of Advertising and Discovery Concepts in Ambient Networks,” IEEE 17th International Symposium on PIMRC, 2006.
Access Broker (Auction-based): Dynamic allocation per Call
2008 KREONET Workshop
Three motivating problems for Cognitive Networks Complex
Large numbers of highly interconnected, interacting elements and instances of self-organization and emergent behavior
Network need to be able to deal with and adapt to complex environment with minimal or zero user interaction
Motivation
17/30
A school of fish
A termite mound
2008 KREONET Workshop
Three motivating problems for Cognitive Networks Wireless and Its heterogeneity
Large numbers of standards IEEE 802.11, Bluetooth, WiMAX, CDMA2000, UMTS…
Ad-hoc networks are highly dynamic should be capable of self-organization In research papers, simulation is usually used because of the
difficulty in using forms of analysis SDR (Software-defined Radio) creates limitless number of
operating states Difficulty in QoS of Layered Architecture
People wants a sort of end-to-end guarantees It is a very difficult research area because most all
networking stacks do not operate on an end-to-end paradigm.
Current approaches are typically reactive.
Motivation
18/30
2008 KREONET Workshop
Cognitive Network (CN) A network composed of elements that, through learning
and reasoning, dynamically adapt to varying network conditions in order to optimize end-to-end performance
Features Decisions are made to meet the requirements of the network
as a whole (not individual network components) A Cognitive Process
perceive conditions, plan, decide, and act on those conditions
Definition
19/30
Global Internet Map(www.siencedaily.com)
[by Ryan Thomas @ Virginia Tech.]
2008 KREONET Workshop
Similarities Operates in parallel to stack Increases information available to participating layers Optimizes on goals that require multiple layers to achieve
Differences Cognition (as opposed to reactive, localized schemes) Multiple and End-to-end goals (as opposed to single goal at
layer level)
Cognitive Network vs. Cross-layering
20/30
[by Ryan Thomas @ Virginia Tech.]
2008 KREONET Workshop
Basic Decision Model OODA Loop [John Boyd] Decision based on observation of
network environments
Implementation It depends on
Goals, Controllable Network Elements System Structure, States
Critical Design Issues Behavior: Selfish vs. Cooperation Computational: Level of ignorance Physical: Amount of control
Cognition Scheme
21/30
[by Ryan Thomas @ Virginia Tech.]
2008 KREONET Workshop
Requirements Layer End-to-End Goals Cognitive Specification Language
Converts end-to-end goals into cognitive elements goals
Cognitive Elements Adapt and learns to make decisions
that meet end-to-end goals
Software Adaptable Network (SAN) API Configurable Elements
Points of network control for cognitive process Network Status Sensors
Reads status of the network
Cognitive Network Framework
22/30
[by Ryan Thomas @ Virginia Tech.]
2008 KREONET Workshop
Cooperative Mobile Robots
Usage Scenarios
Case Study: Mobile Robots & Sensor Network
23/30
[University of Tübingen][USC @ LA]
[Disaster Area]
[Exploring the unknown]
[Robot Army]
[Exploring the unknown]
2008 KREONET Workshop
How to MOVE? Cognition (Perception) of Obstacles and Other Sensors
Supersonic Wave, Artificial Vision, … Force based on Potential Fields
ForceAccelerationVelocityPosition
Sensor Robot Mobility
24/30
2008 KREONET Workshop
How to expand the covering area? A self-deployment algorithm to achieve the max coverage
level Cognition of coverage level in distributed manner
Coverage Level
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Coverage Level: 28.37% Coverage Level: 76.14% Coverage Level: 98.56%
2008 KREONET Workshop
How to make the network connection robust? A self-deployment algorithm to achieve the max
connectivity level Cognition of connectivity level in distributed manner
Connectivity Level
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Avg. # of Neighbor: 2.6 Avg. # of Neighbor: 3.32
Coverage Level Connectivity Level
2008 KREONET Workshop
How to make the overlay level high? An optimized grouping algorithm to achieve the max
energy efficiency
Overlay Level
27/30
70 Active Sensors
Active First Group (of 35 Active Sensors)
Sleep Second Group(of 35 Sleep Sensors)
Active Second Group (of 35 Active Sensors)
Sleep First Group(of 35 Sleep Sensors)
2008 KREONET Workshop
Cognition Scheme in Mobile Sensor Networks
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Sensing Areas,Obstacles, Other Sensors,
Environment Status…
Area Border LocationObstacle Location, Other Sensor Location, Sensing
Range, Communication Range, Current Levels of Coverage, Connectivity, and
Overlay
Optimization Algorithms to
maximize “Coverage Level”,
“Connectivity Level”, and“Overlay Level”
Autonomic Self-deployment of
Sensors
New Position of Sensor Robots
2008 KREONET Workshop
A. Howard, M. J. Mataric, and G. S. Sukhatme, “Mobile Sensor Network Deployment using Potential Fields: A distributed, scalable solution to the area coverage problem,” The 6th International Symposium on Distributed Autonomous Robotics Systems (DARS02), June 2002.
Y. Zou and K. Chakrabarty, “Sensor Deployment and Target Localization based on Virtual Forces,” IEEE INFOCOM 2003, Vol. 2, pp. 1293-1303, March 2003.
S. Poduri and G. S. Sukhatme, “Constrained Coverage for Mobile Sensor Networks,” IEEE International Conference on Robotics and Automation, pp. 165–172, May 2004.
G. Wang, G. Cao and T. L. Porta, “Movement-assisted Sensor Deployment,” In Proc. of IEEE INFOCOM 2004, Vol. 4, pp. 2469-2479, March 2004.
B. Liu, P. Brass, O. Dousse, P. Nain and D, Towsley, “Mobility Improves Coverage of Sensor Networks,” ACM MobiHoc 2005, pp. 300-308, May 2005.
J. Wu and S. Yang, “SMART: A Scan-Based Movement-Assisted Sensor Deployment Method In Wireless Sensor Networks,” In Proc. of INFOCOM 2005, pp.2313-2324, March 2005.
G. Wang, G. Cao, T. L. Porta and W. Zhang, “Sensor Relocation In Mobile Sensor Networks,” In Proc. of INFOCOM 2005, pp. 2302-2312, March 2005.
H. Yu, J. Iyer, H. Kim, E. J. Kim, K. H. Yum and P. S. Mah, “Assuring K-Coverage in the Presence of Mobility in Wireless Sensor Networks,” in Proceedings of IEEE GLOBECOM 2006 (selected for best papers), 2006.
D. Wang, J. Liu and Qian Zhang, “Mobility-Assisted Sensor Networking for Field Coverage,” In Proc. of IEEE GLOBECOM '07. pp. 1190-1194, Nov. 2007.
Wang, H. Wu, and N.-F. Tzeng, “Cross-layer Protocol Design and Optimization for Delay/Fault-tolerant Mobile Sensor Networks, IEEE Journal on Selected Areas in Communications, Vol. 26, No. 5, pp. 809-819, June 2008
References of Mobile Sensor Networks
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2008 KREONET Workshop
Conclusions
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Ambient Networks Network Composition Enhanced Mobility Network Heterogeneity Support
Cognitive Networks Dynamically adapt to varying network conditions Meet the given network requirements and goals
Case Study New Handover Strategy, Business Map, Ambient Network
Broker Cognitive Sensor Network over Mobile Robots